Compressed Fingerprint Matching and Camera Identification via Random Projections
Abstract—Compressed Fingerprint Matching and Camera Identification via Random Projections. Sensor imperfections in the form of photoresponse nonuniformity (PRNU) patterns are a well-established fingerprinting technique to link pictures to the camera sensors that acquired them. The noise-like characteristics of the < Final Year Projects 2016 > PRNU pattern make it a difficult object to compress, thus hindering many interesting applications that would require storage of a large number of fingerprints or transmission over a bandlimited channel for real-time camera matching. We propose to use real-valued or binary random projections to effectively compress the fingerprints at a small cost in terms of matching accuracy. The performance of randomly projected fingerprints is analyzed from a theoretical standpoint and experimentally verified on databases of real photographs.
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